• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4887-4907
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• 2017

Accurate traffic flow forecasting is critical to the development and implementation of city intelligent transportation systems. Therefore, it is one of the most important components in the research of urban traffic scheduling. However, traffic flow forecasting involves a rather complex nonlinear data pattern, particularly during workday peak periods, and a lot of research has shown that traffic flow data reveals a seasonal trend. This paper proposes a new traffic flow forecasting model that combines seasonal relevance vector regression with the hybrid chaotic simulated annealing method (SRVRCSA). Additionally, a numerical example of traffic flow data from The Transportation Data Research Laboratory is used to elucidate the forecasting performance of the proposed SRVRCSA model. The forecasting results indicate that the proposed model yields more accurate forecasting results than the seasonal auto regressive integrated moving average (SARIMA), the double seasonal Holt-Winters exponential smoothing (DSHWES), and the relevance vector regression with hybrid Chaotic Simulated Annealing method (RVRCSA) models. The forecasting performance of RVRCSA with different kernel functions is also studied.

• Particle and aerosol research
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• v.9 no.3
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• pp.163-171
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• 2013

Soot particles emitted from combustion processes are often coated by non-absorbing organic materials, which enhance the global warming effect of soot particles. It is of importance to study the condensation characteristics of soot particles experimentally and theoretically to reduce the uncertainty of the climate impact of soot particles. In this study, the condensational growth of soot particles in a tubular coater was modeled by a one-dimensional (1D) plug flow model and a two-dimensional (2D) laminar flow model. The effects of 2D heat and mass transports on the predicted particle growth were investigated. The temperature and coating material vapor concentration distributions in radial direction, which the 1D model could not accounted for, affected substantially the particle growth in the coater. Under the simulated conditions, the differences between the temperatures and vapor concentrations near the wall and at the tube center were large. The neglect of these variations by the 1D model resulted in a large error in modeling the mass transfer and aerosol dynamics occurring in the coater. The 1D model predicted the average temperature and vapor concentration quite accurately but overestimated the average diameter of the growing particles considerably. At the outermost grid, at which condensation begins earliest due to the lowest temperature and saturation vapor concentration, condensing vapor was exhausted rapidly because of the competition between condensations on the wall and on the particle surface, decreasing the growth rate. At the center of the tube, on the other hand, the growth rate was low due to high temperature and saturation vapor concentration. The effects of Brownian diffusion and thermophoresis were not high enough to transport the coating material vapor quickly from the tube center to the wall. The 1D model based on perfect radial mixing could not take into account this phenomenon, resulting in a much higher growth rate than what the 2D model predicted. The result of this study indicates that contrary to a previous report for a thermodenuder, 2D heat and mass transports must be taken into account to model accurately the condensational particle growth in a coater.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.21 no.9
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• pp.1149-1164
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• 1997

In this study, the applicability of the RNG k-.epsilon. model to the analysis of the complex flows is studied. The governing equations based on a non-orthogonal coordinate formulation with Cartesian velocity components are used and discretized by the finite volume method with non-staggered variable arrangements. The predicted results using the RNG k-.epsilon. model of three complex flows, i.e., the flow over a backward-facing step and a blunt flat plate, the flow around a 2D model car are compared to these from the standard k-.epsilon. model and experimental data. That of the unsteady axisymmetric turbulent flow within a cylinder of reciprocating model engine including port/valve assembly and the spray characteristics within a chamber of direct injection model engine are compared to these from the standard k-.epsilon. model and experimental data. The results of reattachment length, separated eddy size, average surface pressure distribution using the RNG k-.epsilon. model show more reasonable trends comparing with the experimental data than those using the modified k-.epsilon. model. Although the predicted rms velocity using the modified k-.epsilon. model is lower considerably than the experimental data in incylinder flow with poppet valve, predicted axial and radial velocity distributions at the valve exit and in-cylinder region show good agreements with the experimental data. The spray tip penetration predicted using the RNG k-.epsilon. model is more close to the experimental data than that using the modified k-.epsilon. model. The application of the RNG k-.epsilon. model seems to have some potential for the simulations of the unsteady turbulent flow within a port/valve-cylinder assembly and the spray characteristics over the modified k-.epsilon. model.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.652-656
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• 2007

The major streams in South Korea have established the TMDL(Total Maximum Daily Loads) regulation for just 4 years. Traditional concepts in water quality management in South Korea are based upon the selection of a design streram flow which is 10-year averged flow exeedance probability 75%(Q275). That is, a single flow value based upon average long term flow conditions is chosen for application in dilution calculations, permit design, water quality modeling, etc. While these TMDLs seems to satisfy the requirement of the target water quality regulations, they have contributed little to any watershed/waterbody assessment and restoration plans. These types of TMDLs do little to characterize the problems the TMDLs are intended to address. For TMDLs to be more beneficial in the assessment and implementation process, TMDLs should reflect adequate water quality across flow conditions rather than at a single flow value such as average daily flow. In this paper, we developed LDC (load duration curve) methodology for theevaluation of Korean TMDL evaluation based on watershed scaled, physically based on SWAT(Soil and Water Assessment Tool) model.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.45-48
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• 1999

Model predictive control algorithm requires a relevant model of the system to be controlled. Unfortunately, the first principle model describing a polymerization reaction system has a large number of parameters to be estimated. Thus there is a need for the identification and control of a polymerization reactor system by using available input-output data. In this work, the polynomial auto-regressive moving average (ARMA) models are employed as the input-output model and combined into the nonlinear model predictive control algorithm based on the successive linearization method. Simulations are conducted to identify the continuous styrene polymerization reactor system. The input variables are the jacket inlet temperature and the feed flow rate whereas the output variables are the monomer conversion and the weight-average molecular weight. The polynomial ARMA models obtained by the system identification are used to control the monomer conversion and the weight-average molecular weight in a continuous styrene polymerization reactor It is demonstrated that the nonlinear model predictive controller based on the polynomial ARMA model tracks the step changes in the setpoint satisfactorily. In conclusion, the polynomial ARMA model is proven effective in controlling the continuous styrene polymerization reactor.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.2 s.332
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• pp.23-38
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• 2005

The state of channel between two or more wireless terminals is changed frequently due to noise or multiple environmental conditions in wireless network. In this paper, we analyze packet transmission time and queue length in a time-varying channel of packet based Wireless Networks. To reflect the feature of the time-varying channel, we model the channel as two-state Markov model and three-state Markov model Which are transformed to SFG(Signal Flow Graph) model, and then the distribution of the packet transmission can be modeled as Gaussian distribution. If the packet is arrived with Poisson distribution, then the packet transmission system is modeled as M/G/1. The average transmission time and the average queue length are analyzed in the time-varying channel, and are verified with some simulations.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.27 no.7
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• pp.963-972
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• 2003

Performance characteristics of the planar-type solid oxide fuel cell (SOFC) are investigated by the analysis of flow fields coupled with heat and mass transfer phenomena in anode and cathode channels. For these purposes, performance analysis of the SOFC is conducted based on electrochemical reaction phenomena in electrodes and electrolyte coupled with flow fields in anode and cathode channels. In the present study, the isothermal model adopted in the previous paper prepared by the same authors is extended to the non-isothermal model by solving energy equation additionally with momentum and mass transfer equations using CFD technique. It is found that the difference between isothermal and non-isothermal models come from non-uniform temperature distribution along anode and cathode electrodes by solving energy equation in non-isothermal model. Non-uniform temperature distribution in non-isothermal model contributes to the increase of average temperature of the fuel cell and influences its performance characteristics.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.2
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• pp.19-27
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• 2017

Recently, the hydrological model Soil Water Assessment Tool (SWAT) has been applied in many watersheds in South Korea. This study estimated parameters in SWAT for calibrating streamflow in long-term drought periods. Therefore, we focused on the continuous severe drought periods 2014~2015, and understand the model calibrated parameters. The SWAT was applied to a $366.5km^2$ Gongdo watershed by using 14 years (2002~2015) daily observed streamflow (Q) including two years extreme drought period of 2014~2015. The 9 parameters of CN2, CANMX, ESCO, SOL_K, SLSOIL, LAT_TIME, GW_DELAY, GWQMN, ALPHA_BF were selected for model calibration. The SWAT result by focusing on 5 normal years (2002~2006) calibration showed the 14 years average Nash-Sutcliffe model efficiency (NSE) for Q and 1/Q with 0.78 and 0.58 respectively. On the other hand, the 14 years average NSEs of Q and 1/Q by focusing on 2 drought years (2014~2015) calibration were 0.86 and 0.76 respectively. Thus, we could infer that the SWAT calibration trial by focusing on drought periods data can be a good approach to calibrate both high flow and low flow by controlling the 9 drought affected parameters.

• Proceedings of the KOR-KST Conference
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• 1998.10a
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• pp.236-244
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• 1998

When the capacity and traffic operation at signalized intersections are analyzed in Korea, the unprotected left-turn saturation flow rate, which is an important parameter for the analysis, is estimated form the USHCM model. thus, exact analysis of the left-turn is not possible because of the difference of traffic environments between two contries. In order to improve this problem, it is undertaken in this study to develop techniques for the estimation of unprotected left-turn saturation flows based on Korean drivers' data. As study intersections, signalized or unsignalized intersections on the 6, 4 and 2 lane streets are selected. the data for the saturation flow measurement and gap-acceptance behavior analysis are inputed in a notebook computer on the sites. The critical acceptance gaps of the 6, 4, and 2 lane streets are analyzed to be 6.0 secs, 4.6 secs, and 4.3 secs respectively. the average minimum headway of the left-turn vehicle was observed to be 2.6 secs. As the model to estimate unportected left-turn saturation flows, the drew model is recommended for 6 and 4 lane streets, and a graph is suggested for the 2-lane street. As the values of the parameters of the Drew model, the 2.6 secs of this study is recommended for the average minimum headway of the left-turn. But, the critical acceptance gap varies according to the approach speed of opposing traffic and driver population, it requires field survey to measure the gap of an intersection; however, the values of the gaps studied in this study may be used for the general intersections in urban area in Korean.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.3
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• pp.50-60
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• 1998

This paper is concerned with the design of two residual control charts for real-time monitoring of the continuous flow processes. Two different control charts are designed under the situation that observations are correlated each other. Kalman-Filter based model estimation is employed when the process model is known. A black-box approach, based on Back-Propagation Neural Network, is also applied for the design of control chart when there is no prior information of process model. Performance of the designed control charts and traditional control charts is evaluated. Average run length(ARL) is adopted as a criterion for comparison. Experimental results show that the designed control chart using the Neural Network's modeling has shorter ARL than that of the other control charts when process mean is shifted. This means that the designed control chart detects the out-of-control state of the process faster than the others. The designed control chart using the Kalman-Filter based model estimation also has better performance than traditional control chart when process is out-of-control state.